Sara Wade

Reader in Statistics and Data Science


Curriculum vitae


[email protected]


School of Mathematics

University of Edinburgh

Room 5406
James Clerk Maxwell Building, Edinburgh, EH9 3FD



Publications


Leveraging variational autoencoders for multiple data imputation


Breeshey Roskams-Hieter, Jude Wells, Sara Wade

Proceedings of the European Conference on Machine Learning (ECML-PKDD) 2023, Springer Lecture Notes in Computer Science


Fast deep mixtures of Gaussian process experts


C. Etienam, K. Law, S. Wade, V. Zankin

Machine Learning (to appear), Springer, 2023


Bayesian cluster analysis


Sara Wade

Phil. Trans. R. Society, vol. 381(20220149), 2023


Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences


A.K. Leist, M. Klee, J.H. Kim, D.H Rehkopf, S.P.A Bordas, G. Muniz-Terrera, S. Wade

Science Advances, 2022


Bayesian nonparametric scalar-on-image regression via Potts-Gibbs random partition models


Mica Teo, Sara Wade

Springer Proceedings in Mathematics and Statistics, New Frontiers in Bayesian Statistics, BAYSM 2021: Selected Contributions, 2022, pp. 45-56


Colombian women's life patterns: A multivariate density regression approach


S. Wade, R. Piccarreta, A. Cremaschi, I. Antoniano Villalobos

Bayesian Analysis, vol. 17, 2022, pp. 405-433


Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data


W. Yu, S. Wade, H.D. Bondell, L. Azizi

Journal of Computational and Graphical Statistics, vol. 32(2), 2022, pp. 588-600


Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models


C. Gadd, S. Wade, A. Shah

Machine Learning, vol. 110, 2021, pp. 1105-1143


Enriched mixtures of Gaussian process experts.


C. Gadd, S. Wade, A. Boukouvalas

Proceedings of Machine Learning Research, International Conference of Artificial Intelligence and Statistics (AISTATS), vol. 108, 2020, pp. 3144-3154


Posterior inference for sparse hierarchical non-stationary models


K. Monterrubio-Gomez, L. Roininen, S. Wade, T. Damoulas, M. Girolami

Computational Statistics & Data Analysis, vol. 148, 2020, pp. 1-22


Bayesian cluster analysis: point estimation and credible balls (with Discussion)


Sara Wade, Zoubin Ghahramani

Bayesian Analysis, vol. 13, International Society for Bayesian Analysis, 2018, pp. 559 -- 626


Prediction of AD dementia by biomarkers following the NIA-AA and IWG diagnostic criteria in MCI patients from three European memory clinics


A. Prestia, A. Caroli, S. Wade, et al.

Alzheimer's & Dementia, vol. 11, 2015, pp. 1191-1120


A Bayesian nonparametric regression model with normalized weights; A study of hippocampal atrophy in Alzheimer's disease


I. Antoniano-Villalobos, S. Wade, S. G. Walker

Journal of American Statistical Association, vol. 109, 2014, pp. 477-490


Alzheimer's disease biomarkers as outcome measures for clinical trials in MCI


A. Caroli, A. Prestia, S. Wade, et al.

Alzheimer's Disease \& Associated Disorders, vol. 29, 2014, pp. 101-109


Improving prediction from Dirichlet process mixtures via enrichment


S. Wade, D.B. Dunson, S. Petrone, L. Trippa

Journal of Machine Learning Research, vol. 15, 2014, pp. 1041-1071


A predictive study of Bayesian nonparametric regression models


S. Wade, S. G. Walker, S. Petrone

Scandinavian Journal of Statistics, vol. 41, 2014, pp. 580-605


An enriched conjugate prior for Bayesian nonparametric inference


S. Wade, S. Mongelluzzo, S. Petrone

Bayesian Analysis, vol. 6, 2011, pp. 1-28


Thesis



Contributions to Papers with Discussions



Preprints/Submitted Articles


Mixture of Gaussian Process Experts with SMC^2


T. Harkonen, S. Wade, K. Law, L. Roininen

2023



Books


Bayesian Statistics and New Generations: BAYSM 2018, Warwick, UK, July 2-3, Selected Contributions.


Selected Contributors

Springer Proceedings in Mathematics and Statistics, R. Argiento, D. Durante, S. Wade, 2019

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